System and method for providing an aggregation tool

ABSTRACT

Embodiments of the present invention assist in the development, management, and deployment of aggregated data attributes for multiple data sources. One embodiment provides a development interface that allows for elements of attributes, including filters, to be moved into a coding area in which an attribute or an attribute element is being edited. In another embodiment, the user interface presents data fields to assist in the development of filters for multiple data sources with divergent formats. The application further provides a validation interface through which users can validate attributes and trace the results returned by various elements referenced by the attributes under validation. Another embodiment provides a system for managing attributes and deploying them to various systems by creating a deployment file that is used by an attribute calculation system. In one embodiment, the attribute calculation system is a scalable system that dynamically calculates attributes for multiple data sources.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/110,616 filed Dec. 3, 2020, entitled “SYSTEM AND METHOD FOR PROVIDINGAN AGGREGATION TOOL,” which is a continuation of U.S. patent applicationSer. No. 16/843,028 filed Apr. 8, 2020 and which issued as U.S. Pat. No.10,891,691, entitled “SYSTEM AND METHOD FOR PROVIDING AN AGGREGATIONTOOL,” which is a continuation of Ser. No. 16/545,766 filed Aug. 20,2019 and issued as U.S. Pat. No. 10,650,449, entitled “SYSTEM AND METHODFOR PROVIDING AN AGGREGATION TOOL,” which is a continuation of U.S.patent application Ser. No. 16/132,156, filed Sep. 14, 2018 and whichissued as U.S. Pat. No. 10,402,901, entitled “SYSTEM AND METHOD FORPROVIDING AN AGGREGATION TOOL,” which is a continuation of U.S. patentapplication Ser. No. 15/464,089 filed Mar. 20, 2017, and which issued asU.S. Pat. No. 10,078,868, entitled “SYSTEM AND METHOD FOR PROVIDING ANAGGREGATION TOOL,” which is a continuation of U.S. patent applicationSer. No. 14/091,174 filed on Nov. 26, 2013, and which issued as U.S.Pat. No. 9,619,579, entitled “SYSTEM AND METHOD FOR PROVIDING ANAGGREGATION TOOL,” which is a continuation of U.S. patent applicationSer. No. 12/022,954 filed on Jan. 30, 2008, and which issued as U.S.Pat. No. 8,606,666, entitled “SYSTEM AND METHOD FOR PROVIDING ANAGGREGATION TOOL,” which claims the benefit of priority under 35 U.S.C.§ 119(e) of U.S. Provisional Patent Application No. 60/887,523 filed onJan. 31, 2007, the entire contents of which are each hereby incorporatedby reference in their entireties herein and should be considered a partof this application. All publications and patent applications mentionedin this specification are herein incorporated by reference in theirentirety and made a part of this specification to the same extent as ifeach individual publication or patent application was specifically andindividually indicated to be wholly incorporated by reference.

BACKGROUND OF THE INVENTION Field of the Invention

The disclosure relates generally to the field of scoring and predictionand to tools to improve the flexibility and efficiency in generating andevaluating aggregated attributes.

Description of the Related Art

There exists significant interest in information indicative of therelative financial risk or profitability of potential businesstransactions with individuals or other entities. For example, a lendinginstitution is interested in the relative likelihood of a loan recipienttimely and reliably making mutually agreed loan payments. An insurancecompany is interested in the relative likelihood of claims arising froman existing or potential client. Such predictive information is a factorin deciding whether to engage in a particular business transactionand/or the terms under which a transaction takes place.

A large variety of public records and privately developed databases canbe utilized to inform such risk/benefit determinations. For example,credit reporting agencies (CRAs) collect and maintain information on aperson's individual credit history. This information can include a totalcredit line on one or more accounts, current credit balance, creditratios, satisfactorily paid accounts, any late payments ordelinquencies, depth of credit history, total outstanding creditbalance, and/or records of recent and/or historical inquiries into theperson's credit. Governmental motor vehicle agencies generally maintainrecords of any vehicle code violations by a person as well as historiesof reported accidents. Courts will generally maintain records of pendingor disposed cases associated with a person, such as small claimsfilings, bankruptcy filings, and/or any criminal charges. Similarinformation also exists for large and small businesses, such as lengthof the business's existence, reported income, profits, outstandingaccounts receivable, payment history, market share, and so forth.

The extensive amount of data available for any given person or entitymakes the task of evaluating a business decision regarding the person orentity very difficult. Accordingly, such raw data is frequentlyprocessed to facilitate more convenient and rapid financial decisions.For example, a person's raw financial data can be processed to produce a“score” indicative of their relative credit worthiness. Such a score canbe utilized in decisions to extend the person or entity further creditand/or as a factor in determining an interest rate to be charged. Theevaluation of the relative risk/benefit of a given decision is even morecomplex when considering multiple persons simultaneously, such asspouses, partnerships, sole proprietorships, joint ventures, LLCs orother entities. When considering multiple persons, raw data frommultiple sources about each of the individuals may need to be evaluated.

Attributes can be used to calculate various types of scores and in manyinstances may be used on their own to guide business decisions as well.Attributes can be aggregated to target various aspects of credithistories, bankruptcy data, and other types of non-credit-based data.For example, a simple attribute could be “consumers who have opened anew credit line in the last 12 months.” The results of the attributewould be a set of consumers who meets both the criteria of having openeda new credit line and having done so in the last 12 months. Therefore,attributes are important in facilitating the use of raw data for avariety of decisions that financial institutions and other entities mayneed to make.

SUMMARY OF THE DISCLOSURE

Embodiments of the present invention provide systems and methods forcreating, managing, and calculating attributes and filters for multipledata sources. One embodiment is an attribute toolbox (ATB) architecturethat comprises an ATB user interface (ATB UI) and an ATB engine system.

One embodiment of the present invention is a system for creating andusing credit data attributes, comprising an attribute repository forstoring a plurality of credit data attributes, a first applicationserver executing a platform-independent user interface application, acredit data repository, and a second application server executing anattribute calculation engine system, wherein the attribute calculationengine system is configured to retrieve credit data from the credit datarepository and performs calculations on the credit data in accordance tothe attributes in a deployment package generated by the user interfaceapplication. In one embodiment, the user interface application furthercomprises a development interface for editing credit data attributes,wherein the development interface is configured to retrieve the creditdata attributes from the attribute repository for editing and returnedited credit data attributes or newly created credit data attributesfor saving in the attribute repository, a validation interface fortesting credit data attributes, wherein the user interface applicationis configured to execute a validation engine to calculate credit dataattributes on test credit data and display the results on the validationinterface, and a management interface for managing the deployment of thecredit data attributes, wherein the credit data attributes are savedinto a deployment package.

Another embodiment is a system for creating of data attributes,comprising an attribute repository and a user interface applicationconfigured to receive a plurality of requests from users. The attributerepository stores a plurality of data attribute elements, includingattributes, filters, functions, operators, and data definitions. Theuser interface application further comprises a development interface forediting attribute elements, wherein the development interface isconfigured to retrieve attribute elements from the attribute repositoryfor editing and return edited attribute elements or newly createdattribute elements for saving in the attribute repository, and avalidation interface for testing data attributes, wherein the userinterface application is configured to execute a validation processingengine to calculate data attributes on test credit data and display thecalculation results of the individual attribute elements on thevalidation interface.

One embodiment is a system for calculating credit data attributes,comprising at least one credit data repository, a first plurality ofapplication servers executing a plurality of attribute calculationengines, a second plurality of application servers executing a pluralityof data access engines, wherein the data access engines are configuredto access data from the at least one credit data repository, and a thirdplurality of application servers executing a plurality of façadeapplications, wherein the façade applications are configured to receivea plurality of attribute calculation requests from a plurality ofcalling applications, send corresponding requests to the attributecalculation engines and data access engines, and return calculationresults from the attribute calculation engines to the callingapplications.

One embodiment is a method for building attributes for data frommultiple data sources, comprising the steps of defining a plurality offilters, wherein each filter takes into account the format of a datasource among a plurality of data sources, defining a plurality of datasource-independent attributes, wherein the attributes operate on dataselected by the plurality of filters, and creating a deployment packagebased on the plurality of attributes.

One embodiment is a method for calculating data scores based on datafrom multiple data sources, comprising the steps of selecting aplurality of data sets from a plurality of data sources, wherein each ofthe plurality of data sources stores its data in a different format,defining a plurality sets of filters, wherein each set of filters takesinto account the format of each of the plurality of data sources,defining a plurality of data source-independent attributes, extracting asubset of data from each of the selected data sets in accordance to thefilters, calculating the attributes based on the subset of data, andaggregating the results obtained from the step of calculating to createdata scores.

One embodiment of the present invention is a system for creating andusing data attributes, comprising an attribute repository for storing aplurality of data attributes, a first application server executing aplatform-independent user interface application, a data repository, anda second application server executing an attribute calculation enginesystem, wherein the attribute calculation engine system is configured toretrieve data from the data repository and performs calculations on thedata in accordance to the attributes in a deployment package generatedby the user interface application. In one embodiment, the user interfaceapplication further comprises a development interface for editing dataattributes, wherein the development interface is configured to retrievethe data attributes from the attribute repository for editing and returnedited data attributes or newly created data attributes for saving inthe attribute repository, a validation interface for testing dataattributes, wherein the user interface application is configured toexecute a validation engine to calculate data attributes on test dataand display the results on the validation interface, and a managementinterface for managing the deployment of the data attributes, whereinthe data attributes are saved into a deployment package.

BRIEF DESCRIPTION OF THE DRAWINGS

Specific embodiments of the invention will now be described withreference to the following drawings, which are intended to illustrateembodiments of the invention, but not limit the invention:

FIG. 1 illustrates the architecture of the ATB architecture according toan embodiment;

FIG. 2 illustrates the hierarchy and the dependencies of systems,clients, attributes, filters, functions and raw data as used in oneembodiment;

FIG. 3A illustrates an example deployment configuration of the ATB UIaccording to an embodiment;

FIG. 3B illustrates an example deployment configuration of the ATBengine system according to an embodiment;

FIG. 4A is a schematic diagram showing the implementation of the ATB UIaccording to one embodiment;

FIG. 4B is a schematic diagram showing the implementation of the ATBengine system according to one embodiment;

FIG. 5A is an example computer screen showing how attributes are locatedand managed in the ATB UI according to one embodiment;

FIG. 5B is an example computer screen showing the attribute developmentinterface according to one embodiment;

FIG. 5C is an example computer screen showing how functions andoperators can be added to attributes according to one embodiment;

FIG. 6A is an example computer screen showing the filter developmentinterface according to one embodiment;

FIG. 6B is an example computer screen showing how details of a selecteddata source are displayed in the filter development interface accordingto one embodiment;

FIG. 6C is a computer screen showing a search and browse interfacedisplaying how filters are used according to one embodiment;

FIG. 7 is an example computer screen of the validation interface showingthe results of the validation engine according to one embodiment;

FIG. 8A is an example computer screen showing how a client system can becreated in the ATB UI according to one embodiment;

FIG. 8B is an example computer screen showing how attributes can beassociated with a client system for deployment according to oneembodiment;

FIG. 8C is an example computer screen showing how multiple clients andsystems are managed in the ATB UI according to one embodiment;

FIG. 9A is an example computer screen showing how multiple data sourcesare managed in the ATB UI according to one embodiment; and

FIG. 9B is an example computer screen showing show attributes andfilters can be exported according to one embodiment.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Embodiments of the ATB UI system architecture solve many problemsassociated with developing, managing, and deploying attributes. First,many common aggregated attributes are often complex, referencing otherattributes as well as filters that are data format dependent. Thefilters themselves have to be coded to access specific fields within adata source. For example, since each of the main CRAs in the UnitedStates maintains data in a different format, a separate filter is oftenused for each CRA. Therefore, the development of filters and attributesis often a tedious process and syntax errors frequently occur. Thoseskilled in the art will recognize that attributes can be developed fornon-credit data sources, and the challenge of accounting for theindividual formats of non-credit data sources exist as well. In oneembodiment, the ATB UI includes a development interface that allows forfilters and attributes to be moved via the UI, for example, into acoding area in which an attribute or a filter is being edited. Inanother embodiment, the ATB UI provides a filter development interfacethat presents data fields to the user. The interface simplifies the taskof developing filters for multiple data sources that have differentformats by presenting the data fields of the data sources in a graphicaluser interface. The fields can be moved into coding area as well,ensuring that proper data field references are included.

Second, the development of efficient and accurate attributes relies onextensive testing on raw data and constant revisions are made based ontest results. Attributes often reference other attribute elements in along chain of dependencies, including other attributes that may in turnreference numerous filters. For example, in developing an attribute thatuses five other attributes, a developer may have to run numerous testsin order to arrive at the proper weight that should be accorded to eachof the five attributes. In one embodiment, the ATB UI includes avalidation interface that advantageously allows the user to see resultsreturned by each attribute element that is referenced by the attributethat is currently being tested. One embodiment displays the results ofeach filter and each attribute that is referenced by the attribute thatis being validated. This enables the user to quickly determining anyerrors or performance problems hidden in the chain of dependencies. Theuser can, for example, quickly determine that a filter is selecting awrong field or that an attribute calculation is returning erroneous orundesirable results. The interface is particularly helpful in thedevelopment of aggregation attributes, which often reference a largenumber attributes and filters. The ability to trace the results of theindividual elements is invaluable to the development of such attributes.

Third, institutions often require the use hundreds of attributes inmultiple combinations to handle complex analysis and modeling oncredit-based and non-credit based data. As a result, both the creationand maintenance of filters and attributes can require significant timeand effort. Finally, the ability to effectively calculate attributes andscores on data from multiple data sources also presents significantchallenges as well.

Embodiments of the ATB UI and ATB engine system architectures facilitatethe management of the attributes and remove some of the difficultiesthat come with having to manually configure the deployment of attributesin system files. In one embodiment, the ATB UI allows users to associategroups of attributes into a system through a graphical user interface.The ATB UI also provides a comprehensive view of how attributes aredeployed in various systems. Users can quickly and easily view thedependencies between attributes and the associated systems and determinehow editing an attribute will affect the systems in their deploymentscheme. In one embodiment, upon user request the ATB UI willautomatically output a single deployment package including all of theuser's systems, along with the proper associations of attributes,filters, and other configuration information. The deployment package canthen be used in the ATB engine system, a system that performs attributecalculations.

In one embodiment, the ATB engine system is configured to dynamicallyaccess multiple data sources and automatically performs attributecalculations based on the attributes included in the deployment package.In another embodiment, the ATB engine system can calculate theattributes on credit data for a related set of individuals or entities.In one embodiment, both the ATB UI and the ATB engine system areimplemented in a component-based architecture with a high degree offlexibility, maintainability, and scalability. In one embodiment,multiple components can be hosted in a single environment. In anotherembodiment, the components can be distributed across a network with aload balancing server to manage and distribute requests among thecomponents.

FIG. 1 depicts the architecture of an embodiment of the presentinvention. Attribute Toolbox (ATB) architecture 100 includes two maincomponents: an ATB User Interface (ATB UI) module 102 and an ATB enginesystem 104. The ATB UI 102 presents a comprehensive user interfacethrough which users can view, edit, validate, and simulate filters andattributes. The ATB engine system 104 takes the attributes created bythe ATB UI 102, fetches data from the appropriate data sources, andperforms calculations on the fetched data based on those attributes.

ATB UI

As shown in FIG. 1 , the ATB UI 102 includes a presentation component110, a business logic abstraction 112, an attribute/filter managementbusiness logic 114, and a data access layer 116.

Attribute Development

The presentation component 110 presents various user interfaces toassist in the development of filters and attributes and the managementof their deployment to various systems. In one embodiment, thepresentation component 110 further comprises filter and attributedevelopment interfaces 150, a search/browse interface 152, a managementinterface 154, and a validation interface 156. The filter and attributedevelopment interfaces 150 enable users to drag and drop existing datadefinitions, filters, functions, and attributes into a coding area andthereby substantially reducing the time and effort required to locatethe proper elements that need to be added into new filters andattributes. The search interface 152 enables user to search for andbrowse filters, attributes, and clients/systems. The managementinterface 154 allows users to configure clients and systems and providesan interface through which attributes can be associated to systems fordeployment. These user interfaces will be further described inconjunction with FIGS. 5A-9B. In one embodiment, the ATB UI 102 acceptsrequests from client computers 122 and responds by presenting theappropriate user interfaces to the client computers 122.

These user interfaces access objects and methods within the businesslogic abstraction 112 layer, which is an abstraction layer of theattribute/filter management business logic 114. Hence, any futurechanges in the implementation in the attribute/ filter managementbusiness logic 114 will not necessarily necessitate recoding orreconfiguring the presentation component 110. The ATB UI 102 retrievesattributes and filters from the attribute/filter repository 118 throughthe data access layer 116. Likewise, new or edited filters andattributes are saved back to the repository 118. The attributes can bestandardized attributes such as standard aggregation (STAGG) attributescreated by Experian, custom-made attributes, or both.

In one embodiment, the repository 118 implements a version controlfeature so that users of the ATB UI 102 can retrieve previous versionsof attributes and filters. Furthermore, the ATB UI 102 provides alocking mechanism by which users can lock the attributes and filtersthat they are currently editing to prevent other users from changingthem. The locking mechanism and the version control feature enablemultiple users to collaborate on the development of attributes andfilters.

In addition, one embodiment of the ATB UI 102 has user access control.For example, some users may be given rights to execute but not viewattributes. Other users may have full rights to view and edit theattributes. In one embodiment, the user access rights are controlled byspecial serial numbers or passcodes, though it is recognized that avariety of security procedures and methods may be used. A user presentsthe proper serial number or passcode in order to view and editattributes. The modularity of various interfaces, in addition to theuser control feature of ATB UI 102, allows users with various roles tocollaborate on a project. For example, developers of attributes andfilters may be granted full rights to view and modify attributes andfilters, while business analysts may be granted limited rights to deploythe attributes to various systems. In another example, a company thatspecializes in developing attributes and filters may have full accessrights while its customers who purchase the attributes and filters maybe given limited rights to use but not view the attributes and filters.

Testing, Validation and Simulation

One main difficulty with attribute and filter development is thesignificant effort required for validation. Often attribute and filterdevelopers have to test the attributes and filters on sample data andmodify them repeatedly to improve performance and accuracy. In additionto this iterative process, developers have to account for the largenumber of dependencies that can potentially be in any attributes andfilters. FIG. 2 illustrates the potential dependencies as used in oneembodiment. Hierarchy 170 shows that clients are dependent on systems,which in turn are dependent on attributes. An example client may be acredit card company, and the company may have a number of systems forits credit card products. For example, one system may be used to screencommercial card applicants and another may be used to screen consumercard applicants. As such, the two systems have different attributesbecause the screening criteria for these two groups of applicants aredifferent.

Returning to the hierarchy, attributes are further dependent on filters,which in turn are dependent on the raw data definitions. This is becauseattributes are data-independent and filters are data dependent. In oneembodiment, a filter must be defined for each data source. As shown inthe hierarchy 170, each filter can also reference other filters,functions and data definitions. Each attribute, in turn, can reference anumber of filters, functions and other attributes. Thus, an error in adata definition in a single filter can adversely affect all filters thatreference that single filter, and in turn all attributes that referencethose affected filters will be affected as well, and so on.

One embodiment of the ATB UI 102 addresses this difficulty by providinga validation engine 160 that allows for dependency tracing. In oneexample, an attribute A includes three other attributes B, C, D, andattributes B, C and D each additionally has three filters B1, B2, B3 andso on. When the user decides to test attribute A on a test data set inthe validation engine 160, the validation interface 156 shows the userthe results of applying filters B1, B2, B3, C1, C2, C3, D1, D2, and D3to the sample data, as well as the results of calculating attributes B,C, and D. In addition, the validation interface 156 displays the rawdata used in testing. Because each result in the chain of dependency forattribute A is displayed, the user can quickly locate any problem withinthe chain of dependency. For example, the user can see that attribute Bis returning undesirable results, determine that filter B1 is incorrect,and adjust filter B1 to correct the problem. Because the dependenciescan often be far more numerous and complex than this simple example, thevalidation interface 156 provides a powerful tracing tool for developersof attributes and filters for multiple data sources.

In addition to the validation engine 160, embodiments also provide asimulation configuration wherein the user can utilize the ATB UI 102 tosimulate the performance of their filters and attributes to see how theyaffect attribute and score calculations. In one embodiment, the ATB UI102 provides an interface by which a user may connect a customapplication so the user may simulate the attributes and filters createdin the ATB UI 102 in the custom application.

ATB Viewer

Embodiments of the invention also include an ATB Viewer component. TheATB Viewer is a user interface that allows users to “view” parsed rawdata, calculated filter or attribute results. Attributes and filters canbe created and generated and the results can be stored. The results canfurther be returned to a custom/calling application selected by theuser. If the user wishes to view the results immediately, he/she canaccess the ATB Viewer to have a general formatted overview of theresults for a specific test case.

Management and Deployment

The ATB UI 102 allows users to manage the collections of filters andattributes that are slated for deployment in the ATB engine system 104.Users can quickly create attributes and associate a group of attributesfor deployment. For example, a bank user may create twenty attributesfor its credit card operations and another fifty attributes for its homeloan operations. The bank may then associate the twenty attributes to a“Credit Cards” system and the fifty attributes to a “Home Loans” systemsby using the ATB UI 102. The ATB UI 102 then outputs a deploymentpackage 120 to be used by the ATB UI engine system 104, which performscalculations based on these associated attributes included with thedeployment package 120. In one embodiment, the deployment package 120 isgenerated with the proper dependencies among the attributes and filters.Furthermore, the deployment package 120 can accommodate multiplesystems, each with its own associated attributes. This one-stepdeployment function of this embodiment substantially eliminates the costof having to code the dependencies of the attributes manually andenables rapid deployment of multiple systems with a single request sentto the ATB UI 102.

ATB Engine System

The ATB engine system 104 retrieves and parses raw data, calculatesattributes, and returns results. In the illustrated embodiment, the ATBengine system 104 comprises an ATB engine 106 and a data access engine108. In other embodiments, they can be combined into one engine. The ATBengine 106 calculates attributes or scores using data received from thedata access engine 108. In one embodiment, the ATB engine 106 comprisesa parser 162, which reads and parses data. In other embodiments, duringcalculation, the ATB engine 106 reads instructions in a manually createdfile or a deployment file produced by the ATB UI 102. The ATB engine 106then instructs a business rules component 164, which performs the actualcalculations.

In one embodiment, the data access engine 108 accesses the external datasource(s) 140 or reads the data from one or several files (for example,an automatic response format (ARF) file), parses the data, and sends itto the ATB engine 106 for calculation. The data access engine 108comprises a mapper 166 and a communication module 168. The mapper 166handles the mapping of data fields in data sources 140 to objects withinATB engine system 104. The communication module 168 handles the tasks ofcommunicating with various data sources 140. Because data access engine108 accepts a wide variety of data input, it can be configured to accessdata from credit data sources 402 as well as data from non-credit datasources 404, such as a local data source 406. In one embodiment, thelocal data source 406 is a batch XML input. For example, a bank runningan instance of the ATB engine 104 may configure the ATB engine 104 toperform attribute calculations on data from a credit bureau, athird-party data source, and/or its own internal customer data. In oneembodiment, the results of the calculations are sent to a repository 148so the calling application 124 may access them.

Because the ATB engine system 104 can handle multiple data sources, itcan dynamically calculate the attributes across data sources as needed.Embodiments of the ATB engine system 104 can be configured toautomatically calculate attributes across multiple data sources, whetherin response to requests from a plurality of calling applications or alarge volume of batch requests from batch files. The ability to handlecalculations across multiple data sources in accordance to the incomingrequests greatly assist in the evaluation of the relative risk/benefitof a given financial decision that involve multiple persons at the sametime, such as spouses, partnerships, sole proprietorships, jointventures, LLCs or other entities. Thus, unlike prior systems, users ofthe ATB engine system 104 will not have to access the data sourcesindividually and perform attribute calculation for each source and thencombine the results of their calculations. Similarly, the ATB enginesystem 104 will not have to perform an analysis on individualsseparately and then combine the results.

Profile

Embodiments of the ATB engine system 104 additionally includes a profilecomponent. In one embodiment the profile component is part of the façade130. A profile provides the ability to handle simple work flows. Forexample, one work flow may be a decision of call one data source versusanother that depends on the results coming from a previous servicerequest. For example, one profile can include instructions to the ATBengine system 104 to access an alternative data source in case a firstrequest does not return the desired data. The profile workflow logic caninclude a variety of instructions and requests that can be executedbased on the occurrence or non-occurrence of various conditions.Embodiments of ATB engine system include profiles that can handleroll-over logic, ZIP code tables and any other type of logic driven byone or several attribute calculations.

ATB UI Architecture

FIG. 3A depicts an embodiment of the ATB UI web server architecture. Theillustrated ATB UI architecture 200 includes an ATB UI web server 202configured to receive requests from a plurality of workstations or otherremote computing devices 204. In one embodiment, workstations or remotecomputing devices 204 send requests and receive responses via the HTTPor HTTPS protocols, and use web browsers to solicit inputs and displaythe information to the end users. For example, an end user may be a bankthat regularly extends credit to its customers. The bank may be able touse its computers to remotely interact with the ATB UI web server 202 inorder to view, edit, validate, and test its own attributes and filtersstored in relational databases 206. In one embodiment, the ATB UI webserver 202 is a self-contained Ruby on Rails application that acts as aweb server. It communicates via the HTTP or HTTPS protocol in oneembodiment. Syntax checking of attribute codes is accomplished throughjava-script on the client computers. It is recognized that otherapplications, protocols, and languages may be used.

ATB Engine Architecture

FIG. 3B illustrates an embodiment of the ATB engine system architecture.The illustrated ATB engine system architecture 220 includes a callingapplication 222, a load balancer 224, one or more façade web services226, data access engines 228, ATB engines 230, and a data storage 232.In one embodiment, the calling application 222 is an application thatsends calculation requests to the load balancer 224. In otherembodiments, the calling application 222 directly sends requests to thefaçade web service 226. These requests include requests to calculateattributes and scores. For example, a bank may have a callingapplication that sends a request to calculate the number of customerswho have the attribute of recently opening a credit line within the lasttwelve months. In one embodiment, the calling application is acustom-coded application. For example, a mortgage company may have acustom-coded application to process its loan applicants. In anotherembodiment, the calling application is a commercially availableapplication such as Transact by Experian Decision Analytics. It isrecognized that other applications may be used.

In one embodiment, the load balancer 224 receives requests from aplurality of calling applications 222 and distributes those requests toa plurality of the façade web services 226 in order to improve theefficiency of the overall architecture. Each façade web service 226publishes objects and methods available for attribute calculation. Uponreceipt of an incoming request from the calling application 224, thefaçade web service 226 initiates the appropriate remote procedural calls(RPC) over the TCP/IP protocol to either the data access engine 228 orthe ATB engine 230. For example, the façade web service 226 may initiatea first RPC to the data access engine 228 to retrieve the requested datafrom the data storage 232 and then initiate a second RPC to the ATBengine 230 for calculation. The ATB engine 230 then calculates theresults by applying attributes within the deployment package 120 to theretrieved data sets. In one embodiment, a user can use the ATB UI 102 tocreate the deployment package 120. The final results are sent back tothe calling application 222. In the recently opened credit line examplementioned above, the results would be a list of customers who haveopened a recent credit line.

The configuration depicted in FIGS. 3A and 3B is for illustrativepurposes only and those skilled in the art will recognize that anynumber of components of the architecture can be used. In one embodiment,the architecture is designed to be scalable. For example, although notdepicted, a plurality of calling applications and a plurality of creditbureau data sources can be used in the architecture. Moreover, thecomponents can reside in a single computer environment or distributedacross multiple computer environments.

FIG. 4A provides a more detailed depiction of the architecture of theATB UI 102 according to one embodiment. As previously shown in FIG. 1 ,client computers 122 access the ATB UI 102 over one or morecommunication networks. The presentation component 110 presents a userinterface by which users can interact with the ATB UI 102. Except forthe web browsers located on client computers 122, no installed code baseof ATB UI needs to reside on client computers 122. Communications fromthe browser interface to the presentation component 110 occur throughURL navigation or HTTP requests.

The business logic abstraction layer 112 is an abstraction layer of theattribute/filter management business logic 114. The abstraction layer110 further comprises a filter manager 132, an attribute manager 134,and a client manager 136. These managers present objects, and systemsand methods for viewing, editing, and managing filters, attributes, andsystems to which the filters and attributes will employ. The managershave their corresponding counterparts within the business logic 114,namely, a filter business component 142, an attribute business component144, and a client business component 146. The three business componentswork with a repository object 120 within the data access layer 116 fortransactions involving the repository 118. In this example embodiment,the repository 118 comprises a SQLite database server, but those skilledin the art will recognized that other database servers such as Oracle,mySQL, Microsoft SQL Server, and IBM DB2 can be used as well.

The abstraction layer 112 serves as a liaison between the presentationcomponent 110 and the business logic 114. The abstraction layer 112 alsoprovides security enforcement functions in one embodiment. For example,it ensures that attributes are only displayed for the users who have theproper access rights to view them. In one embodiment, the abstractionlayer 112, the business logic 114 and the data access layer 116 areimplemented in a Ruby on Rails environment, which has the advantages ofproviding ease of maintenance and a modular programming construct,though other environments may be used.

As shown in FIG. 4A, the ATB UI 102 further includes a core servicescomponent 254 and a support service component 256. In one embodiment,the core services component 254 is a Rails framework comprising asecurity component 260, an exception component 262, an export/importcomponent 264, and a logger component 266. The security component 260provides the logic for security enforcement, which limits access to theattributes and filters to those users who have the proper levels ofaccess rights. The exception component 262 handles exceptions generatedby any component within the ATB UI 102. The export/import component 264is a data interchange service that supports and provides the capabilityto export and import ATB entities (for example, attributes) from andinto the ATB UI 102. The logger component 266 is served by the Rubylog4r library in one embodiment. It provides the functionality topublish messages to external log stores and to control the type andvolume of data logged. The support service component 256 comprises areporting component 268, which provides a set of pre-defined reportsthat can be run. In one embodiment, the generated reports are templatesfor specification documents and include attributes and related results.

FIG. 4B is a schematic diagram showing the implementation of the ATBengine system 104 according to one embodiment. The façade 130 includestwo methods of accepting requests. It has a web service component 270and a batch component 272. In one embodiment, the web service component270 is supported by a SOAP4R component 294 within technical services288. SOAP4R is a Simple Object Access Protocol (SOAP) implementation inthe Ruby programming language. The web service component 270 thusaccepts SOAP requests from calling applications. Alternatively, thebatch component 272 reads batched requests in a repository 298. In oneembodiment, the repository 298 is a hard drive.

In either case, once an incoming request has been received, the façade130 begins the process of managing the request and performs thenecessary work in order to return a response to the request. First, thefaçade 130 has a message publisher 276 that will publish a message toeither the ATB engine 106 or the data access engine 108. In oneembodiment, the message is a RPC sent via the TCP/IP protocol. Thefaçade 130 includes managing logic that will handle the sequence inwhich RPCs are sent. The façade 130 additionally includes a profilecomponent that handles a variety of work-flow logic as describedearlier.

Both the ATB engine 106 and the data access engine 108 have a messagesubscriber component that subscribes to the message publisher 276. Inthe ATB engine 106, once the message subscriber 278 receives a messagefrom the message publisher 276, it will instruct business component 280to perform calculations. In one embodiment, business component 280further comprises the parser 162 and the business rules component 164.The business rules component 164 performs calculations based on theattributes and filters within deployment package 120, using data parsedby the parser 162. In one embodiment, the business component 280 isimplemented in the Lua scripting language, which provides fast executiontimes and increased performance. This is particularly important in someembodiments because the ATB engine system may be configured to receive ahigh volume of requests from the batch component 272 and to accept alarge number of requests from calling applications through the webservice 270. The façade 130 and the access engine 108 are implemented inthe Ruby programming language in one embodiment.

Access engine 108 also includes the aforementioned message subscriber282 and a data source access framework 284. After the message subscriber282 receives a message from the message publisher 276, it will instructthe data source access framework 284 to access the requested data. Thedata source access framework reads a data source definition file 286 inorder to determine the data formats of the various data sources that arebeing accessed. Finally, technical services 288 include a log4rcomponent that provides logging capability for debugging purposes.

Attribute Interfaces

FIG. 5A is an example computer screen showing the attributesearch/browse interface 152 in the ATB UI 102 according to oneembodiment. As shown, a search panel 302 is provided so users can searchfor attributes by various parameters such as name/keyword, system, andformat. In response, the ATB UI 102 displays a sortable list 304 ofattributes stored in the repository 118 that match the searchparameters. For each attribute, the ATB UI 102 shows the system in whichthe attribute is being deployed, as well as whether the attribute islocked by another user who is viewing or editing it.

The ATB UI 102 facilitates the management of the attributes and removessome of the difficulties of having to manually configure the deploymentof attributes. Because the UI provides a comprehensive view of howattributes are deployed in various systems, users can quickly and easilyview the dependencies between attributes and the associated systems anddetermine how editing an attribute will affect the systems in theirdeployment scheme. In addition, because the name of each attributelisted is a link to the attribute development interface with thatselected attribute shown in a coding area, the users can quickly launchinto the development environment from the list 304.

FIG. 5B is an example computer screen showing how attributes can beedited in the attribute development interface 150 according to oneembodiment. As shown, an example attribute is being edited or created ina coding area 314. Because attributes often reference numerous otherattributes, filters, functions, and operators, the development interface150 provides a panel 312 that lists other attributes, filters,functions, and operators that can be inserted into the coding area 314.This ensures that the newly created attribute or the edited attributewill have the proper dependencies. In one embodiment, the list ispopulated by the attributes and filters retrieved from the repository118. Any attribute or filter listed can be moved (for example, draggedand dropped) into the coding area 314, and a proper reference to thatattribute or filter automatically appears within the coding area 314.

In addition, the panel 312 has a tab area 316, which has two other tabs“filters” and “functions & operators” as shown. A user can select one ofthe other tabs and brings up either the filters or the functions andoperators that are available. Likewise, these elements can be draggedand dropped into the coding area 314 and the proper references areautomatically created. FIG. 5C shows an example of the panel 312 after auser selects the “functions & operators” tab within the tab area 316.Any of the functions and operators shown can be moved (for example,dragged and dropped) into the coding area 314. Therefore, thedevelopment interface 150 enables users to rapidly code new attributesor modify existing attributes with accurate references to otherattributes, filters, functions, and operators.

Filter Interfaces

FIG. 6A is one embodiment of an example computer screen of the filterdevelopment interface 150. Similar to the attribute developmentinterface shown in FIG. 5B, the filter development interface presentsother filters, functions, and operators in a panel 322 that can bedragged and dropped into a coding area 324.

Coding Filters for Various Data Sources

Because of the complexities of database definitions, the task ofdeveloping filters on raw data is often left to programmers. To overcomethis problem, the filter development interface 150 simplifies the taskof developing filters for various data sources by showing the datafields within segments of the data sources. Therefore, in addition tofilters, functions, and operators, the filter development interface hasa “raw data” tab in the tab area 326. As shown in FIG. 6A, the availabledata segments in the data source “Experian” are listed in the panel 322.The fields within the segments are available to be dragged and droppedinto the coding area 324. As shown, the coding area 324 shows the codesthe filter that is being developed.

FIG. 6B is an example computer screen showing how filters can bedeveloped for different data sources in the ATB UI. As shown in FIG. 6B,data fields for a selected segment within a selected data source arelisted in the panel 322. Drop down boxes 320 include a data sourcedrop-down box, a segment drop-down box, and an argument drop-down box.The data source is selected at the data source drop-down box, and thedata segment is selected at the segment drop-down box and so on. In thisexample, the “Experian” data source has been selected and a segment hasalso been selected. In one embodiment, all available valid segmentsassociated with the selected data source are listed in the segmentdrop-down box.

In one embodiment, once a segment is selected, all the available datafields are shown within the panel 322. The user can drag and drop afield into the coding area 324. Through the filter development interface150, a user can easily scan through the available fields within thesegments in a data source and quickly and accurately add the necessaryfields to a filter that is currently being edited in the coding area324. This interface minimizes errors and speeds up the development offilters for multiple data sources with different data formats.

FIG. 6C is a computer screen showing the filter search/browse interface152. Much like the interface shown FIG. 5A for attributes, users cansearch for filters and the search results will be displayed in a listing340. Each filter is listed with status information, whether it has beenlocked by another user for editing, and whether it has been encoded fora particular data source (as indicated by the check marks). Clicking onthe name of the filter will launch a development interface similar tothe one shown in FIG. 6A, where the user can edit the selected filter.

Syntax Checking and Validation

In one embodiment, ATB UI provides a syntax checking engine that checksthe syntax of a filter or an attribute within a current coding area ifrequested by the user. As shown in FIG. 6A, once the user selects a“Check Syntax” button 330, the ATB UI will run a syntax check on eitherthe filter or attribute that is currently being edited. For example,FIG. 6A shows the syntax check window 328 displaying a messageindicating that the syntax check engine has discovered a syntax error online 13 of the example filter. The syntax check engine can likewisecheck for syntax errors within an attribute. Thus users of the ATB UIcan avoid saving invalid filters or attributes. In other embodiments, asyntax check is automatically performed when a user attempts to save afilter or an attribute to the repository 118, or save changes to anexisting filter or attribute.

Besides a syntax checking engine, embodiments of ATB UI also provide thevalidation interface 156 and the validation engine 160 (shown in FIG. 1) through which users can validate attributes against test data. FIG. 7shows an example computer screen of the validation interface 156. Thevalidation interface 156 includes an information/selection area 350,which further includes a data file selector 352 and a data sourceselector 354. Using the data file selector 354, the user can select asample test file including test data for the data source that the userselects in the data source selector 354. In the example shown, the userhas selected a file including sample data from the data source“Experian” to be sent to the validation engine 160. In one embodiment,the validation engine 160 accepts test files for in the ARF format.

In the example shown in FIG. 7 , the validation engine 160, through thevalidation interface 156, provides a result 358 for the selectedattribute “ALL002.” The validation engine 160 has calculated theattribute “ALL002” against the test data and has determined that theresult is 52.0. More importantly, the validation interface 156 furtherincludes a validation table 356 in which a user can examine the raw dataand the dependencies within the attribute that is undergoing validation.The column headings of the validation table 356 show all the dependingfilters and attributes referenced in the code of attribute “ALL002.” Therows of the validation table 356 show raw data from the test file.

The validation interface 156 advantageously allows the user to see exactresults returned by each filter or attribute referenced by the attributethat is being validated. This enables the user to quickly determiningany errors or performance problems hidden in the chain of dependencies.The user can, for example, quickly determine that a filter is selectinga wrong field or that an attribute calculation is returning erroneous orundesirable results. The validation interface 156 is particularlyhelpful in the development of aggregation attributes, which oftenreference a large number attributes and filters.

System Management

FIG. 8A is one embodiment of an example computer screen showing how aclient can be created in the ATB UI. An input interface 360 solicitsconfiguration information that is needed to create a new client. Theinput interface 360 includes a listing of data sources that the newclient will access, as well as a listing of systems that will beassociated with this new client. When the user attempts to save theclient configuration information, the ATB UI will check for errors anddisplay an error message 362 (as shown) if needed.

FIG. 8B is one embodiment of an example computer screen showing howattributes can be associated with a client system for deployment. As anexample, a client who is a bank may wish to deploy various systemsassociated with its needs. The bank may thus have one system thatscreens potential home loan applicants and another system for findingprospective commercial credit card applicants. Because each systemrequires different data and calculations, the bank client may wish toconfigure each one differently. The ATB UI provides an interface 366 toallow a client user to associate various attributes to a system fordeployment. The interface 366 includes an available attribute listing368 and a deployment attribute listing 370. The user can search for andbrowse attributes that are available deployment in the listing 368 andthen add the attributes to the deployment listing 370 by using an arrowselector 372. The attributes will then be slated for deployment for theparticular system.

FIG. 8C is one embodiment of an example computer screen showing howmultiple client system deployments are managed in the ATB UI. A systemlisting 380 lists systems that are available for deployment. Each systemis listed with a name, a historical data entry including the date oflast deployment, status, and the number of associated attributes. Underthe status column, the ATB UI may indicate whether a system is ready ornot ready for deployment. Some systems may not be ready to be deployedbecause they may have attributes with syntax errors or no attributes atall. The system listing 380 provides a way for the user to browsethrough the available systems and quickly determine which are ready fordeployment. Furthermore, the ATB UI provides a link to the attributes sothe user can quickly view or edit the attributes associated with thesystems. The user is also given the option to select multiple systemsfrom the listing 380 and deploy all of them at the same time. Thedeployment package 120 is then automatically created and can be used inATB engine system 104.

Managing Data Sources and Attribute Exports

FIG. 9A is one embodiment of an example computer screen showing howmultiple data sources are managed in the ATB UI 102. The ATB UI 102provides a data source listing 386 that lists the available datasources. Each entry lists the short and long names of the data source aswell as the time when the data source was last modified. The ATB UI 102also provides a data source area 388 that displays the detailinformation of a data source that has been selected. The user can thenview or edit the details of a particular data source, including thelocation of the file from which data can be obtained.

FIG. 9B is one embodiment of an example computer screen shot showing howattributes can be exported to a file. A system listing 390 provides alisting of systems that can be exported. Once exported, the file willinclude all attributes associated with the selected system. The exportfunction allows multiple users from various sites to collaborate on aproject. In one embodiment, users at remote sites without access to thecentralized repository can run their own copies of the ATB UI 102. Forexample, a first user may be developing attributes and filters on alaptop while traveling. The export function enables the first user toexport the attributes and filters and send the export file to a seconduser who runs a different instance of the ATB UI 102 that has aconnection to a centralized repository. The second user will then beable to import the attributes created by the first user and save theattributes to the centralized repository. In one embodiment, the ATB UI102 checks the import file against the repository, so that duplicateattributes are shown to the user. The second user will then have theoption of overwriting the attributes that are in the repository with theimported version. In this manner, numerous users from various remotelocations, even those without connection to a centralized attributerepository, can independently develop attributes and filters and mergetheir work later.

Various Embodiments of System and Method Implementations

In one embodiment, the systems and methods for generating andcalculating attributes may be embodied in part or in whole in softwarethat is running on one or more computing devices. The functionalityprovided for in the components and modules of the computing device(s)may comprise one or more components and/or modules. For example, thecomputing device(s) may comprise multiple central processing units(CPUs) and one or more mass storage device(s), such as may beimplemented in an array of servers.

In general, the word “module,” “application”, or “engine,” as usedherein, refers to logic embodied in hardware and/or firmware, and/or toa collection of software instructions, possibly having entry and exitpoints, written in a programming language, such as, for example, Java,Ruby, Ruby on Rails, Lua, C and/or C++. These may be compiled and linkedinto an executable program, installed in a dynamic link library, or maybe written in an interpreted programming language such as, for example,BASIC, Perl, or Python. It will be appreciated that modules,applications, and engines may be callable from others and/or fromthemselves, and/or may be invoked in response to detected events orinterrupts. Instructions may be embedded in firmware, such as an EPROM.

It will be further appreciated that hardware may be comprised ofconnected logic units, such as gates and flip-flops, and/or may becomprised of programmable units, such as programmable gate arrays orprocessors. The modules, applications, and engines described herein arein certain applications preferably implemented as software modules, butmay be represented in hardware or firmware in other implementations.Generally, the modules, applications, and engines described herein referto logical modules that may be combined with other modules and/ordivided into sub-modules despite their physical organization or storage.

In some embodiments, the computing device(s) communicates with one ormore databases that store information, including credit data and/ornon-credit data. This database or databases may be implemented using arelational database, such as SQLite, Sybase, Oracle, CodeBase, mySQL,and Microsoft® SQL Server as well as other types of databases such as,for example, a flat file database, an entity-relationship database, andobject-oriented database, and/or a record-based database.

In one embodiment, the computing device is IBM, Macintosh, and/orLinux/Unix compatible. In another embodiment, the computing devicecomprises a server, a laptop computer, a cell phone, a Blackberry, apersonal digital assistant, a kiosk, or an audio player, for example. Inone embodiment, the computing device includes one or more CPUs, whichmay each include microprocessors. The computing device may furtherinclude one or more memory devices, such as random access memory (RAM)for temporary storage of information and read only memory (ROM) forpermanent storage of information, and one or more mass storage devices,such as hard drives, diskettes, or optical media storage devices. In oneembodiment, the modules of the computing are in communication via astandards based bus system, such as bus systems using PeripheralComponent Interconnect (PCI), Microchannel, SCSI, Industrial StandardArchitecture (ISA) and Extended ISA (EISA) architectures, for example.In certain embodiments, components of the computing device communicatevia a network, such as a local area network that may be secured.

The computing is generally controlled and coordinated by operatingsystem software, such as the Windows 95, Windows 98, Windows NT, Windows2000, Windows XP, Windows Vista, Linux, SunOS, Solaris, PalmOS,Blackberry OS, or other compatible operating systems. In Macintoshsystems, the operating system may be any available operating system,such as MAC OS X. In other embodiments, the computing device may becontrolled by a proprietary operating system. Conventional operatingsystems control and schedule computer processes for execution, performmemory management, provide file system, networking, and I/O services,and provide a user interface, such as a graphical user interface (GUI),among other things.

The computing device may include one or more commonly availableinput/output (I/O) devices and interfaces, such as a keyboard, mouse,touchpad, microphone, and printer. Thus, in one embodiment the computingdevice may be controlled using the keyboard and mouse input devices,while in another embodiment the user may provide voice commands to thecomputing device via a microphone. In one embodiment, the I/O devicesand interfaces include one or more display device, such as a monitor,that allows the visual presentation of data to a user. Moreparticularly, a display device provides for the presentation of GUIs,application software data, and multimedia presentations, for example.The computing device may also include one or more multimedia devices,such as speakers, video cards, graphics accelerators, and microphones,for example.

In one embodiment, the I/O devices and interfaces provide acommunication interface to various external devices. For example, thecomputing device may be configured to communicate with one or morenetworks, such as any combination of one or more LANs, WANs, or theInternet, for example, via a wired, wireless, or combination of wiredand wireless, communication links. The network communicates with variouscomputing devices and/or other electronic devices via wired or wirelesscommunication links.

Although the foregoing invention has been described in terms of certainembodiments, other embodiments will be apparent to those of ordinaryskill in the art from the disclosure herein. Moreover, the describedembodiments have been presented by way of example only, and are notintended to limit the scope of the inventions. Indeed, the novel methodsand systems described herein may be embodied in a variety of other formswithout departing from the spirit thereof. Accordingly, othercombinations, omissions, substitutions and modifications will beapparent to the skilled artisan in view of the disclosure herein. Forpurposes of discussing the invention, certain aspects, advantages andnovel features of the invention have been described herein. Of course,it is to be understood that not necessarily all such aspects, advantagesor features will be embodied in any particular embodiment of theinvention.

1. (canceled)
 2. A system for generating attributes, the systemcomprising: one or more processors; and non-transitory computer storagecomprising code executable by the one or more processors, the executablecode causing the one or more processors to: receive, via a userinterface, an indication of at least one attribute that relates to atype of credit data; identify a credit data attribute formula expressionbased on the indication of the at least one attribute; generate adeployment package that applies extracted data to the credit dataattribute formula expression; receive at least one attribute score forthe at least one attribute, the at least one attribute score generatedby extracting first data associated with the type of credit data from afirst data source, extracting second data associated with the type ofcredit data from a second data source, and using the deployment packageto apply the extracted first and second data to the credit dataattribute formula expression, the first data and the second data havingdifferent formats; and display, via the user interface, the extractedfirst data, the extracted second data, the credit data attribute formulaexpression, or the at least one attribute score.
 3. The system of claim2, wherein the first data is extracted in accordance with a first filterand the second data is extracted in accordance with a second filter. 4.The system of claim 3, wherein the executable code further causes theone or more processors to display information in a format that allowsidentification of errors in one or more of the first filter, the secondfilter, and the credit data attribute formula expression.
 5. The systemof claim 2, wherein the at least one attribute is data-independent andwherein the first and second filters are data-dependent.
 6. The systemof claim 2, wherein the executable code further causes the one or moreprocessors to display functions and operations associated with the firstfilter or functions and operations associated with the second filter. 7.The system of claim 2, wherein the executable code further causes theone or more processors to calculate a data score based at least in parton the at least one attribute score.
 8. The system of claim 2, whereinthe first filter is configured extract the first data by mapping one ormore data fields in the first data to the type of credit data.
 9. Thesystem of claim 2, wherein the first data source comprises a firstcredit bureau data source and the second data source comprises a secondcredit bureau data source.
 10. A computer-implemented method forgenerating attributes, the computer-implemented method comprising:receiving, via a user interface, an indication of at least one attributethat relates to a type of credit data; identifying a credit dataattribute formula expression based on the indication of the at least oneattribute; generating a deployment package that applies extracted datato the credit data attribute formula expression; receiving at least oneattribute score for the at least one attribute, the at least oneattribute score generated by extracting first data associated with thetype of credit data from a first data source, extracting second dataassociated with the type of credit data from a second data source, andusing the deployment package to apply the extracted first and seconddata to the credit data attribute formula expression, the first data andthe second data having different formats; and display, via the userinterface, the extracted first data, the extracted second data, thecredit data attribute formula expression, or the at least one attributescore.
 11. The computer-implemented method of claim 10, wherein thefirst data is extracted in accordance with a first filter and the seconddata is extracted in accordance with a second filter.
 12. Thecomputer-implemented method of claim 11 further comprising displayinginformation in a format that allows identification of errors in one ormore of the first filter, the second filter, and the credit dataattribute formula expression.
 13. The computer-implemented method ofclaim 10, wherein the at least one attribute is data-independent andwherein the first and second filters are data-dependent.
 14. Thecomputer-implemented method of claim 10 further comprising displayingfunctions and operations associated with the first filter or functionsand operations associated with the second filter.
 15. Thecomputer-implemented method of claim 10 further comprising calculating adata score based at least in part on the at least one attribute score.16. The computer-implemented method of claim 10, wherein the firstfilter is configured extract the first data by mapping one or more datafields in the first data to the type of credit data.
 17. Anon-transitory computer storage medium which stores a client applicationcomprising executable code, the executable code causing a computingdevice to: receive, via a user interface, an indication of at least oneattribute that relates to a type of credit data; identify a credit dataattribute formula expression based on the indication of the at least oneattribute; generate a deployment package that applies extracted data tothe credit data attribute formula expression; receive at least oneattribute score for the at least one attribute, the at least oneattribute score generated by extracting first data associated with thetype of credit data from a first data source, extracting second dataassociated with the type of credit data from a second data source, andusing the deployment package to apply the extracted first and seconddata to the credit data attribute formula expression, the first data andthe second data having different formats; and display, via the userinterface, the extracted first data, the extracted second data, thecredit data attribute formula expression, or the at least one attributescore.
 18. The non-transitory computer storage medium of claim 17,wherein the first data source is selected from the group consisting of acredit bureau source, a non-credit bureau source, and a local datasource.
 19. The non-transitory computer storage medium of claim 17,wherein the first data is extracted in accordance with a first filterand the second data is extracted in accordance with a second filter. 20.The non-transitory computer storage medium of claim 17, wherein theexecutable code further causes the computing device to displayinformation in a format that allows identification of errors in one ormore of the first filter, the second filter, and the credit dataattribute formula expression.
 21. The non-transitory computer storagemedium of claim 17, wherein the executable code further causes thecomputing device to calculate a data score based at least in part on theat least one attribute score.